The study of proteomics and transcriptional regulation involves a broad understanding of the cellular processes governed by the transcriptional products. In a narrow sense, the transcriptome includes only mRNA, but in a broader context, it encompasses all transcriptional products in a cell or tissue, comprising both mRNA and non-coding RNA (ncRNA). Non-coding RNA includes regulatory ncRNA and housekeeping gene RNA, such as tRNA and rRNA. Current research on ncRNA within the transcriptome mainly focuses on small RNAs with regulatory functions (represented by miRNA), long non-coding RNAs (lncRNA), and circular RNAs (circRNA), all of which play roles in the regulation of mRNA.
Long non-coding RNAs (lncRNAs), with a length greater than 200nt, are transcribed from the antisense strand of protein-coding genes and intergenic regions. Initially considered transcriptional "noise" and by-products of RNA polymerase II transcription without biological function, extensive research has revealed their involvement in crucial regulatory processes such as X chromosome inactivation, genomic imprinting, chromatin modification, transcriptional activation, transcriptional interference, and nuclear transport. Although lncRNA sequences exhibit low conservation, about 12% can be found in species other than humans. Mammalian protein-coding genes constitute only 1% of total RNA, making lncRNAs, which can constitute 4%-9% of total RNA, a valuable resource for gene function studies.
Circular RNAs (circRNAs), a special class of RNA, are covalently closed, single-stranded loops that lack a free 5' cap structure and a 3' poly(A) tail. They are resistant to nucleases, making them more stable than linear RNAs. CircRNAs are mainly located in the cytoplasm and can be stored in extracellular vesicles. Most circRNAs exhibit conservation and stability across different species, and their expression shows cell-specific, tissue-specific, and developmental stage-specific patterns.
MicroRNAs (miRNAs), about 20-24 nt in length, are non-coding RNAs with regulatory functions. In animals, they mainly mediate translation suppression by imperfectly pairing with the 3' UTR of target gene mRNA. In plants, they predominantly bind to specific sites in the coding region or UTR of target mRNA through complete or near-complete complementarity, leading to mRNA cleavage or degradation. MiRNAs participate in various cellular activities and biological processes such as cell proliferation and apoptosis, growth and development, stress response, virus defense, and cancer. Since miRNAs cannot encode proteins, they belong to the non-coding RNA family and exhibit conservation across different species. For miRNA data analysis, our company employs the ACGT101-miR software (LC Sciences, Houston, Texas, USA) and utilizes Targetscan, miranda, and PsRobot software for animal and plant sample miRNA target gene prediction, respectively.
With the advancement of high-throughput sequencing and bioinformatics, researchers have discovered many novel non-coding RNAs in high-throughput sequencing data that traditional experiments could not uncover. Besides their pre-transcriptional regulatory functions, a crucial role of these new non-coding RNAs is acting as sponges for miRNAs. These RNAs, termed Competitive endogenous RNAs (ceRNAs), competitively bind miRNAs, leading to the upregulation of miRNA-regulated target genes. Known ceRNAs include lncRNAs and circRNAs, among others. The construction of ceRNA regulatory networks, such as circRNA-miRNA-mRNA or lncRNA-miRNA-mRNA, helps explain this internal competitive mechanism.
Proteins, as the translation products of mRNA, execute specific functions. Therefore, the correlation of transcriptome data with proteome data is commonly performed based on the mRNA-protein translation relationship.
Integrated Analysis of lncRNA, Transcriptome, and Proteome
The regulatory mechanisms of lncRNA on mRNA are mainly classified into two types: cis regulation and trans regulation. Cis regulation, also known as in-line regulation, involves the control of gene expression by lncRNA in proximity to its adjacent genes. The prediction of cis-regulated target genes is primarily based on positional relationships, defining differentially expressed lncRNAs and mRNAs within a 100 kbp range upstream and downstream on the same chromosome. Cis regulation primarily relies on cis-acting elements (cis-acting element), which are sequences located adjacent to the gene and can influence gene expression. These elements include promoters, enhancers, regulatory sequences, and inducible elements. Their role is to participate in the regulation of intranuclear gene expression, and cis-acting elements are typically transcribed into non-coding RNA. The second type of regulation is trans regulation, where lncRNA regulates gene expression across different chromosomes. Trans-regulated target genes are primarily determined based on the free energy required for the formation of secondary structures between lncRNA and mRNA sequences. If the two sequences can form a secondary structure with low free energy, there may be potential interactions between them. Due to the lower accuracy and greater complexity of predicting trans regulation, and the challenges associated with validation, the focus is often on predicting and analyzing cis-regulated differentially expressed mRNAs and lncRNAs. Subsequently, based on the mRNA-protein translation relationship, the association between mRNA and proteins is explored.
Case Study:
Extracellular Vesicles-Mediated Transmission of Viral Genetic Information and Immune Signals May Lead to Immune Suppression and Tolerance in ALV-J Infected HD11 Cells
Research Focus:
Avian Leukosis Virus (ALV) is an oncogenic retrovirus that not only induces immune suppression but also increases host susceptibility to secondary infections. Extracellular vesicles play a crucial role in the signal transduction cascade in response to viral infections. The authors aimed to explore the role of extracellular vesicles in the spread of ALV and subsequent immune responses. They employed RNA-seq and protein relative quantification (iTRAQ) and absolute quantification (PRM) methods to detect differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) secreted by extracellular vesicles after ALV-J injection into macrophages.
Key Findings:
RNA sequencing identified 513 DEGs in infected cells, involving tight junction signaling pathways, TNF signaling pathways, Salmonella infection response, immune response, and other critical cellular processes.
Differential regulation of 843 lncRNAs, with significantly enriched target genes participating in Rap1 signaling, HTLV-I infection, tight junction signaling, and other pathways.
iTRAQ identified 50 DEPs in infected cells, enriched in immune response, antigen processing, MHC protein, and actin-myosin complex formation and transport.
Joint analysis of transcriptome and proteome revealed 337 correlations between RNA and proteins, with 5 being significant. Enrichment on both RNA and protein levels involved cancer pathways, PI3K-Akt signaling, endocytosis, Epstein-Barr virus infection, etc.
Conclusion:
The data suggest that extracellular vesicles act as intercellular signaling messengers in response to viral infections. Extracellular vesicles can carry both viral nucleic acids and proteins, potentially participating in viral infection of other cells and intercellular immune signal transmission. The sequencing results confirm previous research on extracellular vesicles and further indicate their potential role in causing immune suppression and tolerance.
Integrated Analysis of miRNA, Transcriptome, and Proteome
The integrated analysis of miRNA and transcriptome is a systematic dual-level approach for studying the molecular mechanisms of miRNA-mediated gene expression regulation. Proteins serve as the primary executors of cellular functions, and Proteomics is a new discipline in functional genomics that studies the composition, activity patterns, and interactions between proteins at the global level within cells. Proteomics provides a direct description of cellular function and status. The joint analysis of miRNA, transcriptome, and proteomics is a crucial component of systems biology and forms the basis for the current combined analysis of transcriptionally regulated mRNA and proteins.
Case Study:
Comprehensive Analysis of Transcriptomics, miRNA, and Proteomics Reveals the Key Role of miRNA in the Hybrid Vigor of Hybrid Yellow Catfish
Research Focus:
Hybrid vigor is a complex biological phenomenon where offspring produced through hybridization exhibit superior phenotypic traits compared to their parents. Hybrid vigor finds wide applications in agriculture, such as aquaculture; however, its underlying molecular basis remains elusive. To gain extensive molecular insights into the hybrid vigor of fish, the authors used next-generation sequencing and mass spectrometry to analyze the liver tissues of three catfish varieties: Yellow Catfish, Wuchang Bream, and their hybrid offspring "Yellow Optimus." They investigated the expression profiles at the mRNA, miRNA, and protein levels.
Key Findings:
1. The hybrid Yellow Optimus showed easily recognizable patterns of non-additive, homologous expression bias, and expression level dominance at the transcriptional, post-transcriptional, or protein levels. This provides evidence for the widespread existence of dominance models during the hybridization process.
2. These differentially expressed genes/proteins were found to be involved in various critical pathways, including immune defense, metabolism, digestion and absorption, cell proliferation, and development. This indicates their crucial roles in the mechanisms contributing to the phenotypic advantages of hybrid vigor.
3. Many predicted miRNA-mRNA-protein interactions were validated through RT-PCR and PRM. The authors suggest that the high expression of genes/proteins related to growth, nutrition, feeding, and disease resistance in the offspring matches with miRNAs inherited from parents with low expression, providing important insights into the molecular mechanisms underlying hybrid vigor.
Conclusion:
The results highlight the importance of miRNA in shaping the molecular landscape of hybrid vigor in catfish. The study contributes valuable information to our understanding of the molecular basis of hybrid vigor, especially in the context of fish breeding and aquaculture.
Overview of the expressed patterns of genes/miRNAs/proteins (Zhang et al., 2019)
Integrated Analysis of ceRNA, miRNA, Transcriptome, and Proteome
The ceRNA regulatory network (ceRNA networks) refers to the competitive binding of non-coding RNAs such as lncRNA and circRNA to microRNAs, leading to changes in the regulation of target genes by microRNAs. This ultimately manifests at the protein expression level, with microRNAs holding a central position in the ceRNA regulatory network. A single ceRNA can bind to multiple microRNAs, and the sites on ceRNA where microRNAs bind are called microRNA recognition elements (MREs). Typically, a ceRNA has one or more MREs. When the expression level of a ceRNA increases, it competitively binds to microRNAs, leading to an increase in mRNA transcription levels, ultimately resulting in elevated protein expression. Conversely, when the ceRNA expression level decreases, microRNAs are released, leading to a decrease in mRNA transcription levels and, consequently, protein expression.
In summary, the ceRNA regulatory network connects the regulatory interactions of lncRNA and circRNA, along with microRNAs and other non-coding RNAs, to mRNA. This connection extends to other omics such as the proteome and metabolome. In recent years, it has become a focal point for researchers, providing insights into the complex regulatory mechanisms involving non-coding RNAs and their impact on various cellular processes.
Validating mRNA Splicing: Transcriptome vs. Proteome
Alternative splicing allows a single gene to produce multiple mRNA transcripts, and different mRNAs may translate into distinct proteins. Therefore, alternative splicing of a gene can result in the generation of multiple proteins, significantly increasing protein diversity. We identify these novel proteins at the protein level to validate the analysis of alternative splicing in the transcriptome. Creative Proteomics can perform quantitative and differential analysis of various transcripts of the same gene at the transcriptome level and compare the quantitative and differential analysis of various isoforms of the same protein at the translation level.
Transcriptome-Proteome Pathway Correlation Analysis
In both transcriptome sequencing and protein analysis results, Creative Proteomics provides enrichment analysis results for pathways or metabolic pathways of differentially expressed genes or proteins. Comparative analysis is then conducted to associate and analyze the different pathways or metabolic pathways at the two levels. Subsequently, a consistency analysis is performed on the mutual correspondence and expression status of proteins/genes in the associated pathways. This process helps identify several representative key genes/proteins in the pathways. By utilizing the incompleteness and complementarity of these two different expression profiling methods, a comprehensive analysis is conducted to obtain a panoramic view of the expression profile. This systematic and all-encompassing approach is used to study the regulatory mechanisms of important biological processes in animals and plants.
Result Verification
If you want to conduct post-validation, you need to utilize some tools to assist in proving/disproving your hypotheses. Below are some commonly used validation techniques.
RNAomics Validation
- Overexpression Vector: Utilize vectors designed for overexpression to study the impact of increased gene expression.
- Gene Deficient Cell Line: Use cell lines with gene defects to investigate the effects of gene deficiency on your hypothesis.
- Artificial miRNA Inhibitors: Employ artificial miRNA inhibitors to suppress the activity of specific miRNAs and observe the resulting changes.
- Gene Knockdown or Gene Silencing: Perform experiments involving the knockout or silencing of genes to assess their role in the observed phenomenon.
- CLIP-Sequencing (Crosslinking-Immunity Precipitation and High-Throughput Sequencing): Apply CLIP-sequencing to analyze the interactions between RNA and proteins, providing insights into RNA-protein binding events.
Proteomics Validation:
- Antibody-Based Validation Methods: Use techniques like Western Blot, immunohistochemistry (IHC), ELISA, etc., based on antibodies to verify differences in protein expression or modifications between different samples (e.g., experimental and control groups).
- Mass Spectrometry-Based Validation Methods: Employ mass spectrometry-based techniques to validate differences in protein expression or modifications between different samples. PRM (Parallel Reaction Monitoring) is highly recommended. PRM is a high-resolution, high-precision mass spectrometry ion monitoring technique that selectively detects target proteins or peptides (such as post-translationally modified peptides), enabling relative/absolute quantification of the target proteins/peptides.
References
- Ye, Fei, et al. "Exosomes transmit viral genetic information and immune signals may cause immunosuppression and immune tolerance in ALV-J infected hd11 cells." International journal of biological sciences 16.6 (2020): 904.
- Zhang, Guosong, et al. "Integrated analysis of transcriptomic, miRNA and proteomic changes of a novel hybrid yellow catfish uncovers key roles for miRNAs in Heterosis*[S]." Molecular & Cellular Proteomics 18.7 (2019): 1437-1453.
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